David Côté

579 total citations · 1 hit paper
13 papers, 314 citations indexed

About

David Côté is a scholar working on Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, David Côté has authored 13 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 4 papers in Electrical and Electronic Engineering. Recurrent topics in David Côté's work include Network Security and Intrusion Detection (5 papers), Optical Network Technologies (4 papers) and Internet Traffic Analysis and Secure E-voting (4 papers). David Côté is often cited by papers focused on Network Security and Intrusion Detection (5 papers), Optical Network Technologies (4 papers) and Internet Traffic Analysis and Secure E-voting (4 papers). David Côté collaborates with scholars based in Canada, United States and Portugal. David Côté's co-authors include Yan Liu, Wenjie Du, Shervin Shirmohammadi, Michael E. Reimer, Chris Barber, Ryan R. E. Stanley, Corey J. Morris, Craig J. Brown, Thomas S. Bianchi and Paul V. R. Snelgrove and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Ecology and Society.

In The Last Decade

David Côté

12 papers receiving 300 citations

Hit Papers

SAITS: Self-attention-based imputation for time series 2023 2026 2024 2025 2023 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. SAITS: Self-attention-based imputation for time series
    2023 175 citations Wenjie Du, David Côté et al. Expert Systems with Applications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Côté Canada 7 115 73 71 51 46 13 314
Sunitha Basodi United States 7 141 1.2× 68 0.9× 82 1.2× 137 2.7× 61 1.3× 17 428
Zhaoyue Zhang China 8 211 1.8× 81 1.1× 51 0.7× 45 0.9× 65 1.4× 25 398
Wenjia Wu China 11 81 0.7× 110 1.5× 43 0.6× 163 3.2× 41 0.9× 57 345
Xiaochuan Sun China 11 186 1.6× 129 1.8× 27 0.4× 92 1.8× 53 1.2× 37 379
Daw-Ran Liou Taiwan 1 123 1.1× 24 0.3× 37 0.5× 28 0.5× 85 1.8× 2 337
Jianping Zhao China 10 52 0.5× 46 0.6× 20 0.3× 55 1.1× 63 1.4× 63 277
Hans Wehn Canada 10 95 0.8× 32 0.4× 28 0.4× 39 0.8× 23 0.5× 27 283
Yunming Ye China 9 160 1.4× 32 0.4× 34 0.5× 21 0.4× 79 1.7× 21 307

Countries citing papers authored by David Côté

Since Specialization
Citations

This map shows the geographic impact of David Côté's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Côté with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Côté more than expected).

Fields of papers citing papers by David Côté

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Côté. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Côté. The network helps show where David Côté may publish in the future.

Co-authorship network of co-authors of David Côté

This figure shows the co-authorship network connecting the top 25 collaborators of David Côté. A scholar is included among the top collaborators of David Côté based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Côté. David Côté is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Du, Wenjie, David Côté, & Yan Liu. (2023). SAITS: Self-attention-based imputation for time series. Expert Systems with Applications. 219. 119619–119619. 175 indexed citations breakdown →
2.
Bianchi, Thomas S., Craig J. Brown, Paul V. R. Snelgrove, et al.. (2023). Benthic Invertebrates on the Move: A Tale of Ocean Warming and Sediment Carbon Storage. Limnology and Oceanography Bulletin. 32(1). 1–5. 6 indexed citations
3.
Côté, David, et al.. (2023). Toward a Superintelligent Action Recommender for Network Operation Centers Using Reinforcement Learning. IEEE Access. 11. 20216–20229. 4 indexed citations
4.
Esfandiari, Babak, et al.. (2023). Importance of Optical Metrics for IGP Configuration Change Prediction. 26–33.
5.
Côté, David, et al.. (2022). Stateless ARE: Action Recommendation Engine without Network State Measurement. 1–6. 1 indexed citations
6.
Rangeley, Robert, et al.. (2022). Megabenthic biodiversity in culturally and ecologically important coastal regions of Northern Labrador. Ecology and Society. 27(4). 5 indexed citations
7.
Shirmohammadi, Shervin, et al.. (2021). Forecasting Video QoE With Deep Learning From Multivariate Time-Series. IEEE Open Journal of Signal Processing. 2. 512–521. 17 indexed citations
8.
Côté, David, et al.. (2021). Machine Learning-Based Network Status Detection and Fault Localization. IEEE Transactions on Instrumentation and Measurement. 70. 1–10. 13 indexed citations
9.
Du, Wenjie, David Côté, Chris Barber, & Yan Liu. (2021). Forecasting loss of signal in optical networks with machine learning. Journal of Optical Communications and Networking. 13(10). E109–E109. 6 indexed citations
10.
Côté, David, et al.. (2021). A Machine-Learning-Based Action Recommender for Network Operation Centers. IEEE Transactions on Network and Service Management. 18(3). 2702–2713. 11 indexed citations
11.
Shirmohammadi, Shervin, et al.. (2020). Deep Learning-Based Fault Localization in Video Networks Using Only Client-Side QoE. IEEE Transactions on Artificial Intelligence. 1(2). 130–138. 8 indexed citations
12.
Reimer, Michael E., et al.. (2019). Practical considerations for near-zero margin network design and deployment [Invited]. Journal of Optical Communications and Networking. 11(9). C25–C25. 10 indexed citations
13.
Côté, David. (2018). Using Machine Learning in Communication Networks [Invited]. Journal of Optical Communications and Networking. 10(10). D100–D100. 58 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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